The capacity to innovate is commonly regarded as a key response mechanism, acritical organisational competence for success, even survival, for organisationsoperating in turbulent conditions. Understanding how innovation works, therefore,continues to be a significant agenda item for many researchers. Innovation, however, isgenerally recognised to be a complex and multi-dimensional phenomenon.Classificatory approaches have been used to provide conceptual frameworks fordescriptive purposes and to help better understand innovation. Further, by the facilityof pattern recognition, classificatory approaches also attempt to elevate theorising fromthe specific and contextual to something more abstract and generalisable. Over the last50 years researchers have sought to explain variance in innovation activities andprocesses, adoption and diffusion patterns and, performance outcomes in terms ofthese different ‘types’ of innovation.Three generic approaches to the classification of innovations can be found in theliterature (innovation newness, area of focus and attributes). In this research, severallimitations of these approaches are identified: narrow specification, inconsistentapplication across studies and, indistinct and permeable boundaries betweencategories. One consequence is that opportunities for cumulative and comparativeresearch are hampered.The assumption underpinning this research is that, given artefact multidimensionality,it is not unreasonable to assume that we might expect to see the diversity of attributesbeing patterned into distinct configurations. In a mixed-method study, comprising ofthree empirical phases, the innovation classification problem is addressed through thedesign, testing and application of a multi-dimensional framework of innovation,predicated on perceived attributes. Phase I is characterised by an iterative process, inwhich data from four case studies of successful innovation in the UK National HealthService are synthesised with those drawn from an extensive thematic interrogation ofthe literature, in order to develop the framework.The second phase is concerned with identifying whether or not innovations configureinto discrete, identifiable types based on the multidimensional conceptualisation ofinnovation artefact, construed in terms of innovation attributes. The framework isoperationalised in the form of a 56-item survey instrument, administered to a sampleconsisting of 310 different innovations. 196 returns were analysed using methodsdeveloped in biological systematics. From this analysis, a taxonomy consisting of threediscrete types (type 1, type 2 and type 3 innovations) emerges. The taxonomy providesthe basis for additional theoretical development. In phase III of the research, the utility of the taxonomy is explored in a qualitative investigation of the processesunderpinning the development of exemplar cases of each of the three innovation types.This research presents an integrative approach to the study of innovation based on theattributes of the innovation itself, rather than its effects. Where the challenge is tomanage multiple discrete data combinations along a number of dimensions, theconfigurational approach is especially relevant and can provide a richer understandingand description of the phenomenon of interest. Whilst none of the dimensions thatcomprise the proposed framework are new in themselves, what is original is theattempt to deal with them simultaneously in order that innovations may be classifiedaccording to differences in the way in which their attributes configure. This moresensitive classification of the artefact permits a clearer exploration of relationshipissues between the innovation, its processes and outcomes.